Matthew Schurr
About Matthew Schurr
Matthew Schurr is a Senior Software Engineer at ExtraHop Networks, where he has worked since 2016. He previously served as a Teaching Assistant at Rice University and interned at Google, contributing to various software development projects.
Work at ExtraHop
Matthew Schurr has been employed at ExtraHop Networks as a Senior Software Engineer since 2016. In this role, he has contributed to multiple projects that enhance the functionality of the ExtraHop Discover and Trace Appliances. His work includes the implementation of the GeoIP Trigger API, which allows customers to create location-based metrics and dashboards. He also developed crash and power failure recovery features for the Trace Appliance, enabling minimal data loss during system failures. Additionally, he improved the Trace Appliance's packet look back duration by implementing functionality for writing to external storage devices.
Education and Expertise
Matthew Schurr earned a Bachelor of Science (B.S.) in Computer Science from Rice University, where he studied from 2012 to 2016. His education provided a strong foundation in software engineering principles and practices. During his time at Rice University, he also served as a Teaching Assistant from 2013 to 2014, gaining experience in mentoring and supporting students in their academic pursuits.
Background
Before joining ExtraHop, Matthew Schurr completed two internships at Google. In 2014, he worked as a Software Engineering Intern in Mountain View, California, where he contributed to the development of Network Live Activity Maps by implementing back-end and assisting with front-end components. In 2015, he interned in New York City, where he developed a protocol parser for WebSockets in the ExtraHop Discover Appliance, facilitating metric collection and trigger execution on protocol events.
Achievements
Matthew Schurr has made significant contributions to the ExtraHop Trace Appliance, including enhancing its search index recovery speed, which reduced recovery time from over 60 minutes to less than 1 minute. He achieved a reduction in search index memory usage by over 90% through index compression and migration, which extended the storage capacity of the appliance. Additionally, he created a distinct count metric type using HyperLogLog, improving port scan anomaly detection within the Discover Appliance.